Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "65" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 49 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 47 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2459864 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.127127 | 0.111385 | 0.604070 | -0.945521 | 1.323114 | 0.878160 | -0.612278 | -0.122030 | 0.7039 | 0.6844 | 0.4223 | nan | nan |
| 2459863 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.465482 | 0.859948 | -1.067477 | -0.332527 | 2.157762 | 0.963461 | -0.142118 | -0.208496 | 0.6977 | 0.6736 | 0.4109 | nan | nan |
| 2459862 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.425008 | 0.555360 | 1.211662 | -0.651272 | 2.297593 | 2.734061 | -0.243196 | -0.681106 | 0.6831 | 0.7035 | 0.4286 | nan | nan |
| 2459861 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.471699 | 0.188859 | -0.869086 | -0.106059 | 1.747251 | 0.833464 | 0.677050 | -0.152488 | 0.7063 | 0.6776 | 0.4346 | nan | nan |
| 2459860 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.390425 | 0.270292 | 0.500957 | -0.378229 | 2.331120 | 1.888801 | -0.345092 | -0.162713 | 0.7138 | 0.6818 | 0.4237 | nan | nan |
| 2459859 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.402059 | 0.071989 | -0.784347 | -0.201575 | 1.496445 | 0.567763 | -0.003042 | 0.195539 | 0.7214 | 0.6887 | 0.4137 | nan | nan |
| 2459858 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 6.950634 | 5.785288 | -0.688175 | -0.106757 | 2.345662 | 1.669624 | 4.156878 | 0.165506 | 0.6765 | 0.6454 | 0.4056 | 3.090538 | 2.674973 |
| 2459857 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 15.480300 | 11.468764 | 3.332823 | 2.480472 | 5.463598 | 5.281327 | 6.258351 | 9.258039 | 0.0246 | 0.0230 | 0.0010 | nan | nan |
| 2459856 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 3.43% | 0.00% | 0.735662 | 0.519174 | 0.244515 | -0.072132 | 2.273272 | 1.023456 | -0.610265 | 0.758315 | 0.7219 | 0.7094 | 0.4127 | 1.558700 | 1.459254 |
| 2459855 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 4.58% | 0.00% | 0.702623 | 0.522479 | 0.391122 | -0.292966 | 2.385389 | 0.658346 | -0.086479 | 0.148617 | 0.7045 | 0.7287 | 0.4439 | 1.568104 | 1.415315 |
| 2459854 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 8.93% | 0.00% | 0.373717 | -0.177030 | 0.589289 | -0.653318 | 1.966202 | 0.407740 | -0.319995 | -0.017210 | 0.7153 | 0.7438 | 0.4520 | 1.525630 | 1.387867 |
| 2459853 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.56% | 0.672932 | -0.055290 | 0.637187 | -0.861816 | 1.462488 | 0.868705 | 0.939821 | 0.266464 | 0.7420 | 0.6987 | 0.4322 | 1.720238 | 1.525303 |
| 2459852 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 8.65% | 2.16% | 2.804368 | 0.099511 | -0.041217 | -0.815922 | 2.232816 | 0.452264 | 0.572080 | 0.231909 | 0.8231 | 0.8337 | 0.2530 | 2.994308 | 3.169087 |
| 2459851 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 11.76% | 0.53% | 1.110128 | 0.977636 | 0.459352 | -0.735025 | 1.569866 | 1.829715 | -0.568159 | -0.409922 | 0.7557 | 0.7467 | 0.3570 | 1.462907 | 1.452551 |
| 2459850 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 18.02% | 0.00% | 0.535993 | 0.141372 | 0.625979 | -0.715267 | 2.882253 | 1.060632 | -0.641435 | 0.292744 | 0.7407 | 0.7612 | 0.3713 | 1.530816 | 1.388508 |
| 2459849 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 16.67% | 0.00% | 1.107768 | 0.431630 | 2.528287 | -0.709898 | 3.438399 | 0.842090 | -0.585734 | 0.418329 | 0.7374 | 0.7518 | 0.3769 | 1.524704 | 1.393801 |
| 2459848 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 1.405419 | 1.099091 | -0.429053 | 0.851609 | 4.916090 | 1.442057 | -0.093509 | 0.517547 | 0.7176 | 0.7517 | 0.4004 | 3.273630 | 3.147474 |
| 2459847 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 3.21% | 0.53% | 1.419579 | 1.134864 | -0.768063 | 1.039339 | -0.398543 | 0.951053 | -0.265275 | -0.653996 | 0.7295 | 0.6909 | 0.4383 | 1.553196 | 1.375275 |
| 2459846 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.421979 | 0.284789 | -0.843718 | 0.467823 | 5.290601 | 2.424975 | 0.238694 | 0.196202 | 0.8350 | 0.6810 | 0.4955 | 3.646640 | 3.469256 |
| 2459845 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.350711 | 1.769240 | 0.918019 | 0.794503 | 3.708045 | 0.464286 | 0.568509 | 0.040045 | 0.7265 | 0.7464 | 0.3898 | -0.000000 | -0.000000 |
| 2459844 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 31.193234 | 21.359866 | 23.746052 | 19.770097 | 4.419338 | 9.105425 | 9.911426 | 13.528697 | 0.0237 | 0.0221 | 0.0011 | nan | nan |
| 2459843 | digital_ok | 0.00% | 0.66% | 0.66% | 0.00% | 16.30% | 0.54% | 1.798346 | 1.299077 | 1.941395 | 0.334179 | 1.180271 | 1.322938 | -0.717562 | 0.059013 | 0.7401 | 0.7506 | 0.3929 | 1.736824 | 1.668273 |
| 2459840 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 63.364609 | 43.732215 | 15.097443 | 12.420945 | 5.591395 | 10.238367 | 14.987285 | 19.358546 | 0.0212 | 0.0200 | 0.0011 | nan | nan |
| 2459839 | digital_ok | 100.00% | - | - | - | - | - | 16.185127 | 10.933218 | 36.022929 | 30.166516 | 2.198461 | 3.098146 | 20.304239 | 25.141572 | nan | nan | nan | nan | nan |
| 2459838 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | 0.000000 | 0.000000 |
| 2459836 | digital_ok | - | 100.00% | 100.00% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.0315 | 0.0325 | 0.0012 | nan | nan |
| 2459835 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | 0.770940 | -0.501308 | 0.452759 | 1.048607 | 1.128945 | 1.186641 | 0.350287 | 1.760346 | 0.0312 | 0.0326 | 0.0011 | nan | nan |
| 2459833 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 7.268483 | 4.951129 | 8.100656 | 6.032004 | 0.598366 | 3.499289 | 9.049926 | 9.902152 | 0.0240 | 0.0247 | 0.0014 | nan | nan |
| 2459832 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 2.451882 | 0.440759 | 1.640359 | 0.481415 | 1.902845 | 0.431243 | 0.434365 | -0.246724 | 0.8127 | 0.5393 | 0.5788 | 1.755691 | 1.673605 |
| 2459831 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 16.770867 | 11.179507 | 38.995028 | 32.968505 | 3.291103 | 3.586342 | 14.680715 | 18.217097 | 0.0217 | 0.0204 | 0.0011 | nan | nan |
| 2459830 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 2.823811 | 0.508971 | 2.813860 | 1.015217 | -0.478316 | -0.359441 | -0.404734 | 0.978218 | 0.8130 | 0.5571 | 0.5552 | 1.788937 | 1.471153 |
| 2459829 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 3.121926 | 1.678685 | 3.395589 | 0.889498 | 6.448648 | 1.880517 | 1.340321 | 3.022060 | 0.7614 | 0.6784 | 0.4059 | 16.884646 | 12.527787 |
| 2459828 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 1.725999 | 0.800343 | 0.991574 | 1.254019 | 0.481143 | 0.188995 | 0.306652 | 5.271475 | 0.8107 | 0.5589 | 0.5435 | 3.928716 | 3.958239 |
| 2459827 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 1.773040 | 0.998446 | 0.752244 | 0.933862 | 1.138058 | 0.341263 | 0.221993 | 0.391873 | 0.7625 | 0.6812 | 0.4098 | 1.744443 | 1.451002 |
| 2459826 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 1.919196 | 0.731884 | 0.332046 | 1.030114 | -0.200937 | 0.012712 | -0.538800 | 1.203613 | 0.8051 | 0.5652 | 0.5294 | 1.540953 | 1.095291 |
| 2459825 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 1.641329 | 0.517295 | 0.050980 | 0.899554 | -1.104587 | -0.798372 | -0.587694 | -0.645477 | 0.8060 | 0.5798 | 0.5216 | 2.435664 | 2.048121 |
| 2459824 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.506881 | 0.520192 | 0.039779 | 0.432235 | 0.730148 | 1.877708 | -0.493325 | -0.013008 | 0.7284 | 0.7475 | 0.3632 | 1.978673 | 1.967137 |
| 2459823 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 1.322386 | 0.468146 | -0.014150 | 1.325904 | 0.006220 | -0.818015 | -0.110821 | 1.701625 | 0.7707 | 0.6586 | 0.4566 | 1.145444 | 1.149831 |
| 2459822 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 1.923386 | 0.603692 | 0.771584 | 1.394641 | -0.544073 | -0.048728 | -0.513923 | -0.498171 | 0.8026 | 0.5985 | 0.5142 | 2.008400 | 1.680546 |
| 2459821 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 1.927442 | 0.601883 | 0.903663 | 1.030409 | 0.002434 | 0.273569 | -0.868955 | -0.329530 | 0.7957 | 0.6067 | 0.5187 | 1.985305 | 1.709552 |
| 2459820 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 1.873824 | 1.175073 | 0.899729 | 1.019517 | 2.791665 | 2.554826 | -0.620034 | 1.033217 | 0.7705 | 0.6938 | 0.4233 | 1.586750 | 1.439806 |
| 2459817 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 1.386875 | 0.186864 | 0.743964 | 0.921706 | 0.612392 | 0.870702 | 0.053573 | 0.292609 | 0.8019 | 0.6411 | 0.5092 | 1.870958 | 1.740115 |
| 2459816 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | 0.000000 | 0.000000 |
| 2459815 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 1.502299 | 0.311024 | -0.055417 | 0.956659 | 0.228638 | 0.399638 | -0.527083 | 1.119844 | 0.7980 | 0.6575 | 0.5156 | 1.650544 | 1.447447 |
| 2459814 | digital_ok | 0.00% | - | - | - | - | - | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459813 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 3.235581 | 2.205855 | 0.635277 | 0.277433 | 6.086700 | 4.840369 | 0.488911 | 4.087753 | 0.7942 | 0.7401 | 0.3997 | 10.246985 | 8.584275 |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Temporal Variability | 1.323114 | 0.111385 | 0.127127 | -0.945521 | 0.604070 | 0.878160 | 1.323114 | -0.122030 | -0.612278 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Temporal Variability | 2.157762 | 0.465482 | 0.859948 | -1.067477 | -0.332527 | 2.157762 | 0.963461 | -0.142118 | -0.208496 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | nn Temporal Variability | 2.734061 | 0.425008 | 0.555360 | 1.211662 | -0.651272 | 2.297593 | 2.734061 | -0.243196 | -0.681106 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Temporal Variability | 1.747251 | 0.188859 | 0.471699 | -0.106059 | -0.869086 | 0.833464 | 1.747251 | -0.152488 | 0.677050 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Temporal Variability | 2.331120 | 0.390425 | 0.270292 | 0.500957 | -0.378229 | 2.331120 | 1.888801 | -0.345092 | -0.162713 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Temporal Variability | 1.496445 | 0.402059 | 0.071989 | -0.784347 | -0.201575 | 1.496445 | 0.567763 | -0.003042 | 0.195539 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Shape | 6.950634 | 5.785288 | 6.950634 | -0.106757 | -0.688175 | 1.669624 | 2.345662 | 0.165506 | 4.156878 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Shape | 15.480300 | 11.468764 | 15.480300 | 2.480472 | 3.332823 | 5.281327 | 5.463598 | 9.258039 | 6.258351 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Temporal Variability | 2.273272 | 0.735662 | 0.519174 | 0.244515 | -0.072132 | 2.273272 | 1.023456 | -0.610265 | 0.758315 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Temporal Variability | 2.385389 | 0.522479 | 0.702623 | -0.292966 | 0.391122 | 0.658346 | 2.385389 | 0.148617 | -0.086479 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Temporal Variability | 1.966202 | -0.177030 | 0.373717 | -0.653318 | 0.589289 | 0.407740 | 1.966202 | -0.017210 | -0.319995 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Temporal Variability | 1.462488 | -0.055290 | 0.672932 | -0.861816 | 0.637187 | 0.868705 | 1.462488 | 0.266464 | 0.939821 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Shape | 2.804368 | 2.804368 | 0.099511 | -0.041217 | -0.815922 | 2.232816 | 0.452264 | 0.572080 | 0.231909 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | nn Temporal Variability | 1.829715 | 1.110128 | 0.977636 | 0.459352 | -0.735025 | 1.569866 | 1.829715 | -0.568159 | -0.409922 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Temporal Variability | 2.882253 | 0.535993 | 0.141372 | 0.625979 | -0.715267 | 2.882253 | 1.060632 | -0.641435 | 0.292744 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Temporal Variability | 3.438399 | 1.107768 | 0.431630 | 2.528287 | -0.709898 | 3.438399 | 0.842090 | -0.585734 | 0.418329 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Temporal Variability | 4.916090 | 1.099091 | 1.405419 | 0.851609 | -0.429053 | 1.442057 | 4.916090 | 0.517547 | -0.093509 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Shape | 1.419579 | 1.134864 | 1.419579 | 1.039339 | -0.768063 | 0.951053 | -0.398543 | -0.653996 | -0.265275 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Temporal Variability | 5.290601 | 0.421979 | 0.284789 | -0.843718 | 0.467823 | 5.290601 | 2.424975 | 0.238694 | 0.196202 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Temporal Variability | 3.708045 | 1.769240 | 2.350711 | 0.794503 | 0.918019 | 0.464286 | 3.708045 | 0.040045 | 0.568509 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Shape | 31.193234 | 31.193234 | 21.359866 | 23.746052 | 19.770097 | 4.419338 | 9.105425 | 9.911426 | 13.528697 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Power | 1.941395 | 1.299077 | 1.798346 | 0.334179 | 1.941395 | 1.322938 | 1.180271 | 0.059013 | -0.717562 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Shape | 63.364609 | 63.364609 | 43.732215 | 15.097443 | 12.420945 | 5.591395 | 10.238367 | 14.987285 | 19.358546 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Power | 36.022929 | 10.933218 | 16.185127 | 30.166516 | 36.022929 | 3.098146 | 2.198461 | 25.141572 | 20.304239 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | nn Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | nn Temporal Discontinuties | 1.760346 | -0.501308 | 0.770940 | 1.048607 | 0.452759 | 1.186641 | 1.128945 | 1.760346 | 0.350287 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | nn Temporal Discontinuties | 9.902152 | 4.951129 | 7.268483 | 6.032004 | 8.100656 | 3.499289 | 0.598366 | 9.902152 | 9.049926 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Shape | 2.451882 | 2.451882 | 0.440759 | 1.640359 | 0.481415 | 1.902845 | 0.431243 | 0.434365 | -0.246724 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Power | 38.995028 | 16.770867 | 11.179507 | 38.995028 | 32.968505 | 3.291103 | 3.586342 | 14.680715 | 18.217097 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Shape | 2.823811 | 2.823811 | 0.508971 | 2.813860 | 1.015217 | -0.478316 | -0.359441 | -0.404734 | 0.978218 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Temporal Variability | 6.448648 | 1.678685 | 3.121926 | 0.889498 | 3.395589 | 1.880517 | 6.448648 | 3.022060 | 1.340321 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | nn Temporal Discontinuties | 5.271475 | 0.800343 | 1.725999 | 1.254019 | 0.991574 | 0.188995 | 0.481143 | 5.271475 | 0.306652 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Shape | 1.773040 | 1.773040 | 0.998446 | 0.752244 | 0.933862 | 1.138058 | 0.341263 | 0.221993 | 0.391873 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Shape | 1.919196 | 0.731884 | 1.919196 | 1.030114 | 0.332046 | 0.012712 | -0.200937 | 1.203613 | -0.538800 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Shape | 1.641329 | 0.517295 | 1.641329 | 0.899554 | 0.050980 | -0.798372 | -1.104587 | -0.645477 | -0.587694 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | nn Temporal Variability | 1.877708 | 0.506881 | 0.520192 | 0.039779 | 0.432235 | 0.730148 | 1.877708 | -0.493325 | -0.013008 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | nn Temporal Discontinuties | 1.701625 | 0.468146 | 1.322386 | 1.325904 | -0.014150 | -0.818015 | 0.006220 | 1.701625 | -0.110821 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Shape | 1.923386 | 1.923386 | 0.603692 | 0.771584 | 1.394641 | -0.544073 | -0.048728 | -0.513923 | -0.498171 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Shape | 1.927442 | 0.601883 | 1.927442 | 1.030409 | 0.903663 | 0.273569 | 0.002434 | -0.329530 | -0.868955 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Temporal Variability | 2.791665 | 1.873824 | 1.175073 | 0.899729 | 1.019517 | 2.791665 | 2.554826 | -0.620034 | 1.033217 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Shape | 1.386875 | 1.386875 | 0.186864 | 0.743964 | 0.921706 | 0.612392 | 0.870702 | 0.053573 | 0.292609 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | nn Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Shape | 1.502299 | 0.311024 | 1.502299 | 0.956659 | -0.055417 | 0.399638 | 0.228638 | 1.119844 | -0.527083 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 65 | N03 | digital_ok | ee Temporal Variability | 6.086700 | 2.205855 | 3.235581 | 0.277433 | 0.635277 | 4.840369 | 6.086700 | 4.087753 | 0.488911 |